Utility providers face the problem of satisfying consumer demand for electrical energy during peak and off-peak demand periods. Total electrical energy demand varies significantly between the peak and off-peak demand periods. For example, energy demand typically peaks on a hot summer afternoon as a result of the widespread simultaneous operation of air conditioning systems, and energy demand subsequently drops during the off-peak period of the late evening. To accommodate very high peak demands, utility providers face options of investing in additional power generating capacity, buying power from other utilities having excess capacity, or using an electrical load management system to control the amount of electrical energy distributed over the electrical distribution network during peak energy demand periods by electrical load reductions, commonly referred to as load shedding.
As of this writing, many utility providers have turned to load shedding as the most viable option to address very high peak demands. Load shedding usually comprises “direct load control” or demand response programs. Direct load control is a method where utility providers may interrupt the loads of their consumers during critical demand times.
In exchange for permitting this interruption, the consumer generally receives more favorable energy rates because that customer is not consuming energy generated by the auxiliary or back-up devices of the utility provider which may be needed during very high peak energy demands.
As one example of load shedding, a homeowner on a direct load control program may find his air conditioner periodically interrupted on hot summer days by a switch operated by the utility provider. In exchange for permitting this remote operation of the switch, the homeowner's utility bill is generally lower than that of customers not on the direct load control plan. Other incentives include home owner compensation in exchange for participating in the program. This load cycling by the utility provider may reduce overall energy consumption when electricity demand is highest, thereby improving grid reliability and reducing energy costs for the utility provider.
There are typically two methods used to reduce HVAC load in a demand response program: a cycling method and temperature set back. The cycling method generally includes shutting off the compressor on a periodic basis that reduces the normal run time of the compressor. This method provides the utility with a known and controllable load reduction since the amount of run time reduction is directly controllable by the command issued.
A problem associated with the cycling method is that the indoor temperature will usually continually rise during the control event and there is no temperature cap to limit this rise. Depending on how long the control events lasts, on how well the home is insulated, and the outdoor temperature, the indoor temperature may raise to a level that is uncomfortable for the customer. Customers may be more reluctant to sign up for cycling programs if the temperature rise during the event is too high or unknown, thus driving up the cost for customer acquisition and results in higher program costs.
A second method for load reduction is to perform a temperature setback. Utilities can send a setback value, say thirty-four degrees, to all the thermostats so that the HVAC is now regulating the indoor temperature at a higher value than what the customer has set it for. Every degree of temperature setback usually results in some energy reduction from the HVAC system. This method may limit the indoor temperature rise—making it easier to market to customers.
To address the cycling problem, utility providers often establish maximum (cooling) and minimum (heating) temperature limits for the space being serviced by the HVAC system. So for a cooling scenario in the summer months, utility providers allow the load shedding program to be overridden or suspended temporarily when the maximum temperature is reached. In this way, the HVAC system may be provided with power and start operating again to cool the space coupled to the HVAC system. The problem with this solution is that the maximum and minimum temperature limits are set to be identical across all customers. Also, the direct load control program may resume once the temperature of the space has fallen below the maximum temperature.
Using identical maximum and minimum temperature limits across all customers by a utility provider does not account for differences in the construction of the various spaces of the customers being serviced. For example, a first building may be poorly insulated and may reach the maximum temperature on a hot day very quickly within an hour or two. Similarly, a second building may be well insulated but its space conditioning load may be improperly sized for the space.
Meanwhile, a third building may be well insulated and may have properly sized space conditioning load. In this situation, the third building may not reach the maximum temperature on a hot day until several hours, significantly more than the first building with poor insulation and/or a poorly sized space conditioning load. A person residing in the first building will be less likely to subscribe to the direct load control program of the utility provider since the first building will reach a maximum and uncomfortable temperature very quickly and frequently during a operation of a direct load control program.
Another method to reduce customer discomfort is to allow the customer to override that event when the indoor temperature rises too high. This reduces the energy reduction that the utility is seeking.
Another solution that has been proposed to address the problems associated with cycling load control is to modify cycling within the direct load control program and to resume normal cycling when a maximum or minimum temperature has been avoided. Cycling generally refers to a set period or length in time in which a space conditioning load is provided with power and without power. For example, a first cycle may have a predetermined length of thirty minutes. During this thirty minute window, power for the space conditioning load may be stopped for the first twenty minutes of the window, while during the remaining ten minutes of the window, power may be supplied to the space conditioning load.
One solution that has been suggested to address the discomfort by a consumer when a maximum temperature for a space has been reached on a hot day is to modify the first cycle noted above. The first cycle may be modified so that there is less time in which power is not provided to the space conditioning load. For example, the off-power time may be adjusted from twenty minutes to fifteen minutes so that power is now supplied to the space conditioning load for fifteen minutes instead of the lower value of ten minutes.
While this proposed solution of modifying cycling of a direct load control program may help a consumer to cool a space to avoid a maximum temperature on a hot day, the proposed solution requires that the normal cycling be resumed once the maximum temperature is avoided. As noted above, if a building is poorly insulated and/or it has an improperly sized space conditioning load, the consumer will likely experience the maximum temperature quickly and frequently while the direct load control program is being executed. Indoor temperatures may swing wildly as the cycling value changes from the original to the modified program and back.
Accordingly, what is needed is a system and method that may overcome the problems associated with conventional direct load control programs that do not account for differences that may exist across consumers with respect to insulation and/or sizes for the space conditioning loads. What is needed is a system that allows a customer or utility to control a maximum temperature rise under a direct load control program. Another need exists for a system that advises a utility provider on how many customers actually reached this maximum temperature rise to optimize their load control program.